Performance Analysis of MRC under Spatially Correlated Interference using Mixture-based Method

TL;DR

This paper introduces a mixture-based analytical method to accurately evaluate the outage probability of N-antenna MRC receivers under spatially correlated interference, overcoming the limitations of traditional PPP-based models.

Contribution

It develops a novel mixture-based approach for tractable analysis of interference correlation in wireless systems with arbitrary antenna numbers.

Findings

The mixture-based method provides highly accurate outage probability estimates.

Analytical results are validated through Monte Carlo simulations.

The approach simplifies the analysis of correlated interference for N > 2 antennas.

Abstract

Effect of interference correlation on wireless systems is often studied by modeling the locations of interferers as a Poisson Point Process (PPP). However, in many cases, the complicated nature of this correlation limits the analytical tractability of the PPP-based approach. For example, for an interference-aware $N$-antenna Maximum-Ratio Combining (MRC) receiver, the analytical expression for outage probability is available only for $N=2$. For $N>2$, the exact analysis using standard PPP-based approach becomes intractable because of which one has to either resort to bounds or to simulations. In this letter, we overcome this issue and derive the MRC outage probability for an arbitrary $N$ by employing the mixture-based method of modeling the correlation in the interference powers. This method offers a much simpler analytical structure to the correlated interference, thereby lending analytical tractability to such analyses. The mixture parameter ($q$) is tuned based on the matching of joint Signal-to-Interference Ratio (SIR) statistics, which results in a very accurate mixture-based result. The tightness of these approximations is verified using Monte Carlo simulations.